(a) Field of the Invention
The present invention according to a first exemplary embodiment relates to a signal measuring/diagnosing system and method that are capable of measuring and diagnosing a target signal.
More particularly, the first exemplary embodiment of the present invention relates to a signal measuring/diagnosing system and method that are capable of measuring and diagnosing signals obtained from a sensor attached to measure mechanical system operation performance and conditions. For example, the first exemplary embodiment of the present invention of the present invention relates to a signal measuring/diagnosing system and method that are capable of signal measuring/diagnosing while effectively reducing a volume of the storage medium. According to the first exemplary embodiment, instead of saving all the signals measured from a target system which requires a long measurement time, signal waveforms are analyzed and conditions of the target system and measurement system are self-monitored and diagnosed to only store the corresponding signals when the possibility of failure of the target system is high.
Further, the first exemplary embodiment of the present invention relates to a signal measuring/diagnosing system and method that is capable of reducing expert labor required in observing, selecting, and analyzing the signal waveforms after the signals are measured, and that is capable of preventing the occurrence of opportunity loss of a measurement test by promptly stopping inaccurate measurements in the case where inaccurate measurements continue due to a partial problem in the measurement system.
The present invention according to a second exemplary embodiment relates to a monitoring method and system that monitors a mechanical system which performs a predetermined goal. More particularly, it relates to a monitoring method and system that is capable of accurately monitoring and diagnosing conditions of a target system in different use environments by appropriately classifying signals measured from the target system operating under complex driving conditions according to different driving conditions.
The present invention according to a third exemplary embodiment relates to a method and system for monitoring, diagnosing, and analyzing states of vehicle chassis components, and more particularly, to a method and system for monitoring, diagnosing, and analyzing the states of the vehicle chassis components which diagnose and/or monitors and/or analyzes the states of the vehicle chassis components directly related to vehicle safety based on signals from a knuckle movement-detecting sensor and various vehicle sensors.
The present invention according to a fourth exemplary embodiment relates to a bearing endurance test monitoring method that may accurately monitor an endurance test of bearings such as a hub-bearing.
(b) Description of the Related Art
In the related art to the first exemplary embodiment, an endurance test is often conducted directly in a field for research or new product development. For example, in the case of vehicles, before a newly developed vehicle is sold to users, it goes through months of road tests, whereby a series of measured signals about vehicle performance and durability are stored in memory. Later, the memory is downloaded onto a general-purpose computer (PC), etc., and each signal waveform is individually analyzed and edited until only the waveforms and analysis results of significance are drawn. Many experts invest a lot of time in this process.
Furthermore, in the cases in which a wire of the sensor short-circuits and thus proper measurement of signal waveforms is prevented, an incomplete test is conducted for a long period of time leading to a loss of important test opportunity. However, a method for effectively improving a test which uses such a conventional measurement system is not being developed.
For example, in the case of railway vehicles, there are instances in which securing the tracks and the opportunity to conduct the test itself are very important depending on implementation of the test. However, for such tests, a measurement system with a watchdog function that can adequately diagnose the test conditions on site is not being developed.
In addition, large and costly mechanical systems such as generators have a life span of about 20 to 30 years, and a failure during operation leads to an exceedingly large loss from the inability to generate power due to downtime. To counteract this effectively, it is necessary to monitor different conditions, and in case of damage, it is necessary to minimize the downtime by notifying the user or supervisor through early auto-detection and quickly preparing for damage repair.
In the case of offshore wind power generators, due to difficult access, downtime can last about 45 days unless a barge for repair has been pre-arranged. However, in the case in which the possibility of damage is detected early, repair is possible in about one week leading to a very substantial economic effect.
For this reason, a condition-monitoring system has been recently mandatorily installed at the offshore wind power generators.
Nevertheless, in the case of the conventional condition-monitoring system in which it is important to have early damage detection by signal processing the signal waveforms received from the sensors into different types and analyzing them, there are many instances in which signal waveforms from sensors are inaccurately analyzed due to disturbances from the surrounding environment and noise caused by system operation.
When such misdiagnosis continues, users and supervisors become mistrustful of the condition-monitoring system, and even when a real failure occurs, they sometimes do not prepare for it or even turn off the switch for the condition-monitoring system.
Therefore, it is very important to raise diagnosis reliability of the state monitoring system as much as possible.
However, since the condition-monitoring system is required to handle and analyze signal waveforms for an extremely long period, only the representative value from the signal waveform analysis is substantially stored in a database (DB)
The representative value includes a standard deviation for signal waveforms, a maximum value, etc.
However, to implement diagnoses of higher reliability, it is necessary to conduct a rigorous analysis requiring a longer time. However, unlike a measurement system which stores all signal waveforms, the condition-monitoring system can't store all signal waveforms but can only store the representative value due to a data storage volume problem it has when used for a long period.
However, misdiagnosis may occasionally occur because conducting a further more rigorous analysis using only the representative value is not possible.
Meanwhile, Korean Patent No. 10-052234 (Korean Patent Application No. 10-2003-7000040), which discloses a prior art, relates to managing and diagnosing conditions of equipment. According to Korean Patent No. 10-052234, when information corresponding to an abnormal level is extracted out of the information collected about the equipment driving conditions, the advanced analysis diagnosis unit of the equipment diagnosis center processes an advanced analysis/diagnosis procedure and swiftly notifies the user about the best response information regarding the equipment that is determined to be abnormal. Furthermore, by allowing the advanced analysis diagnosis unit to upload a program for analyzing equipment management data on the user equipment monitoring unit, the user can analyze a large volume of raw data without transmitting it to the equipment diagnosis center.
However, Korean Patent No. 10-052234 still has a problem in that it has no processing unit that selectively stores or organizes the raw data with its large data volume, making a detailed analysis of measurements done over a long-period difficult.
Mechanical systems such as wind power generators, which correspond to the second exemplary embodiment, generally operate depending on complex driving conditions.
Therefore, in the case of a wind power generator which is an example of a mechanical system, classification of measured signals in which a number of revolutions of the driving system, external wind speed, generated power, etc. are simultaneously considered is needed in order to accurately monitor the conditions of the driving system.
However, in the case of conventional wind power generators, since only generated power is considered in monitoring the driving conditions, signals measured according to an abnormal sudden external wind may be misdiagnosed as failure signals.
In order to prevent said misdiagnosis and increase the reliability of diagnosis, multi-dimensional signal monitoring capable of considering different driving conditions simultaneously and databases therefor are needed.
The types of target systems and their related parameters that need measured signal classification according to the multi-dimensional driving conditions include the following.
First, the parameters that affect the movement of the above-described wind power generator's gear box and bearing are a number of revolutions of a rotor, external wind speed, generated power, etc. Second, there are a number of revolutions of a hub bearing of a vehicle and a railway vehicle, radial directional load (acceleration) thereof, axle directional load (acceleration) thereof, etc. Third, there are a number of revolutions of a rotor of a large generator (thermal and nuclear power generators), steam temperature/pressure thereof, generated power thereof, etc. Fourth, there are a number of revolutions of a rolling mill and radial directional load (acceleration) thereof, etc.
The above-described target systems are driving systems that are relatively provided with numerous condition-monitoring devices attached thereto, and improvement of accuracy of diagnosis about them is important.
In the above-described conventional target systems, when the parameters for driving conditions are selected, a knowledge database, which is an expert system for diagnosis, is established first
In other words, signals about the driving conditions of the target system in a healthy condition without failure are measured, and a database is established about the parameters selected as physical quantities.
However, since the conventional signal classification method classifies the measured signal values based on one-dimensional parameters, it is difficult to accurately determine monitoring stability and the cause of diagnosis.
For example, in the case of the conventional wind power generators, a root-mean-square (RMS) of the driving system vibrating signals measured for monitoring the conditions of teeth of a gear and the bearing are classified into predetermined steps (e.g. six steps).
However, in such a case, although there is a sudden fast external wind or a local gale, when the generated power is not high, the monitoring system may measure a relatively high value and mistake it as damage in the target system.
When such a misdiagnosis is repeated, the system operator may mistrust the reliability of the monitoring system, and in extreme cases, the operator may ignore the diagnosis results.
When the user, the operator, and the manager mistrust the monitoring system, they may not prepare to respond or may turn off the monitoring system, and not use it even though a real failure occurs in the target system.
Therefore, it is important to improve diagnosis reliability of the monitoring system as much as possible.
In the art related to the disclosed third exemplary embodiment, the internal diagnosis system for the vehicle is limited in application to components of the engine control unit needed for measuring the sensors of the control systems and the exhaust gas. For example, when the sensors of the control systems are abnormal, since control itself may not be substantially performed, an anti-skid braking system (ABS), a traction control system (TCS), and a vehicle dynamic control system (VDC) check the sensors thereof.
In the case of exhaust gas, since relevant laws are very strict, an alarm device which self-diagnoses the sensors and the exhaust gas-measuring device of the engine control system and notifies the operator in case of a problem is forced to be installed by the laws.
However, when defects exist at many safety components of the vehicle, although the defects may lead to a fatal accident, there are almost no cases of effectively monitoring or diagnosing them.
When pressure of tires is low, vehicle rollover accidents may occur, thus mandatory installation of a device monitoring the pressure of the tires is being regulated globally.
Furthermore, since accidents due to sudden acceleration and vehicle defects are frequent at present, it is necessary to apply a substantial black box that can simultaneously more effectively monitor and diagnose vehicle defects from a larger range, and objectively analyze the causes of an accident as it is done in aircraft accidents.
Meanwhile, many aircraft technologies are being applied to vehicles. For example, starting with the application of ABS to vehicles in 1980, many other aircraft technologies are being applied for vehicle control.
As described above, control systems are varied, and many vehicle components are provided with sensors. Additionally, when a low-cost sensor is installed, a method is needed to simultaneously monitor and diagnose vehicle safety components, as in aircrafts, so the vehicle can always be driven in a safe condition and to accurately and objectively determine the cause of an accident in case it occurs.
On the other hand, according to domestic and international statistical analysis data on the causes of vehicle accidents, it can be seen that components that lead to accidents are mostly chassis components associated with a steering system, a suspension system, and a brake system.
In other words, the chassis components are highly related to safety.
In the related art to the disclosed fourth exemplary embodiment, as is well-known to a person of ordinary skill in the art, the goal of a bearing endurance test is to test whether there is enough endurance performance for a given load and driving conditions.
The test condition, for example, includes two types of axial and radial loads, and a most basic bearing endurance test and/or a bearing endurance test monitoring method is to check the endurance time by consistently selecting the important test parameters, such as the two types of loads and a number of revolutions thereof.
Generally, in order to perform an elaborate bearing endurance test, the two types of loads (axial load and radial load) and the number of revolutions thereof are changed to emulate real use conditions.
Meanwhile, a failure can occur during the bearing endurance test. In a method for detecting the failure, if a temperature sensor and/or a vibration sensor adhered near the outer ring of the test target bearing detects a temperature equal to or greater than a predetermined value or if the vibration RMS value exceeds a predetermined value, it is determined to be a failure and the test is stopped.
However, the temperature and/or the RMS need to be substantially high or great in order to correctly detect a failure in the endurance test. However, if the temperature and/or the RMS are substantially high or great, there is a problem that the failure is detected after the endurance test has been performed for a considerable time.
In such cases where a failure is detected late, there may be following problems.
Namely, a manufacturing company's main goal for conducting an endurance test is to confirm whether performance requirements are satisfied. However, a more important goal is to accurately analyze the causes of the failure so as to improve the design and manufacturing process and ultimately be able to swiftly develop products with satisfactory performance. However, this may not be easy.
Prior art documents related to the exemplary embodiments of the present invention are the following. 1. Korean Patent No. 10-0522342 (2005 Oct. 11)
2. Korean Patent Laid-Open Publication No. 10-2013-0064344 (2013 Jun. 18.)
3. Patent Laid-Open Publication No. 10-2003-0014417 (2003 Feb. 17.)
The above information disclosed in this Background section is only to enhance the understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.